Public clouds are increasingly being utilized to meet the information technology needs of individuals, business enterprises and other users. Such public clouds may be shared by a very large number of users, and therefore performance can be highly unpredictable. For example, performance of a given public cloud may vary significantly from user to user and also from processing job to processing job for a given user, based on a variety of factors that are usually not readily apparent to the users. Moreover, users often have multiple options in terms of the particular public clouds to utilize for different processing jobs, but no reliable mechanism is available to assess the relative advantages of these public clouds as applied to a particular processing job.
Even though data may be available within a cloud-based information processing system that could assist users in assessing public cloud performance, such data is often in large part kept confidential by the corresponding cloud service provider, and therefore is typically limited to use by internal information technology administrators and other personnel of the cloud service provider.
Related problems include a general inability in conventional cloud-based information processing systems for users to adequately oversee certain aspects of processing job execution that are of particular interest to them.
Accordingly, users can often feel as though they have insufficient control over any of their processing jobs that are executing in the public cloud. This has become a barrier to more widespread adoption of public cloud processing models.
A need therefore exists for improved techniques for user interaction with public clouds and other cloud-based processing systems.